The letter comes after Benioff joked at a company event on Monday that ICE was monitoring international employees in attendance, sparking immediate backlash. Employees at Salesforce are circulating an internal letter to chief executive Marc Benioff calling on him to denounce recent actions by US Immigration and Customs Enforcement, prohibit the use of Salesforce software by immigration agents, and back federal legislation that would significantly reform the agency. The letter specifically cites the "recent killings of Renee Good and Alex Pretti in Minneapolis" as catalysts, calling them the "devastating indictment of a system that has discarded human decency." It's unclear how many signatories the letter has received so far. The letter, which has not been reported on previously, is being organized amid Salesforce's annual leadership kickoff event this week in Las Vegas.

A memo obtained by WIRED confirms Denise Dresser's departure from Slack. She is now headed to OpenAI. Slack CEO Denise Dresser is leaving the company and joining OpenAI as the company's chief revenue officer, multiple sources tell WIRED. Marc Benioff, the chief executive of Salesforce, which owns Slack, shared news of Dresser's departure in a message to staff on Monday evening. At OpenAI, Dresser will manage the company's enterprise unit, which has been growing rapidly this year.

Will AI mean the end of call centres? Ask ChatGPT whether AI will replace humans in the customer service industry, and it will offer a diplomatic answer, the summary of which is they will work side by side. Humans though, are not so optimistic. Last year, the chief executive of Indian technology firm Tata Consultancy Services, K Krithivasan, told the Financial Times that AI may soon mean that there is minimal need for call centres in Asia. Meanwhile, AI will autonomously resolve 80% of common customer service issues by 2029, predicts business and technology research firm Gartner.

Salesforce's CEO backtracks after saying Trump should send troops into San Francisco In tech this week: The CEO of the city's largest private employer apologizes, Amazon Web Services' outage and OpenAI's Sora makes waves What I'm watching this week: South Park's caricature of Peter Thiel and his obsession with the antichrist . Read our reporting on the show's inspiration: Thiel's bizarre off-the-record lectures on the subject. And now, let's get into things. The co-founder and CEO of Salesforce, said last week that Donald Trump should make good on his threats to send the US national guard into San Francisco, despite resistance from local leaders. Even Marc Benioff's own public relations manager was aghast at his remarks, according to the New York Times .

Governance of data, compliance, and business privacy matters, particularly for healthcare and finance businesses. Since the recent emergence of AI enterprise AI assistants enhancing business productivity, safeguarding private data and compliance is now a priority. With the implementation of AI assistants across the enterprise, the zero data retention can be achieved by implementing zero data retention policies by Large Language Model businesses like Open AI and Anthropic and Meta. In this work, we explore zero data retention policies for the Enterprise apps of large language models (LLMs). Our key contribution is defining the architectural, compliance, and usability trade-offs of such systems in parallel. In this research work, we examine the development of commercial AI assistants with two industry leaders and market titans in this arena - Salesforce and Microsoft. Both of these companies used distinct technical architecture to support zero data retention policies. Salesforce AgentForce and Microsoft Copilot are among the leading AI assistants providing much-needed push to business productivity in customer care. The purpose of this paper is to analyze the technical architecture and deployment of zero data retention policy by consuming applications as well as big language models service providers like Open Ai, Anthropic, and Meta.

OpenAI revealed last week the custom AI tools it uses internally. The news sent some software companies into turmoil. Allan Thygesen, the CEO of Docusign, was not particularly concerned when he saw the news last week that OpenAI had created an internal tool called DocuGPT . He might have preferred that OpenAI choose a different name for its contracting tool. But still, he thought, DocuGPT barely scratched the surface of what Docusign can do.

Salesforce has slashed another 4,000 jobs from its customer support workforce as the tech giant doubles down on artificial intelligence, even as the company reports strong financial results. AI agents now reportedly handle about one million customer conversations. In a recent episode of The Logan Bartlett Show, CEO Marc Benioff justified the cuts by saying he "needs less heads" as Salesforce invests heavily in AI across its operations. Earlier this year, Benioff boasted that AI was already doing 30 to 50 percent of the work, which he framed as efficiency gains – a 17 percent cost reduction achieved after shedding 1,000 people in February. On Wednesday, the Slack owner reported revenue topped 10.2bn for the quarter ending July 31, up 10 percent from the same period last year.

The Internet is poised to host billions to trillions of autonomous AI agents that negotiate, delegate, and migrate in milliseconds and workloads that will strain DNS-centred identity and discovery. In this paper, we describe the NANDA index architecture, which we envision as a means for discoverability, identifiability and authentication in the internet of AI agents. We present an architecture where a minimal lean index resolves to dynamic, cryptographically verifiable AgentFacts that supports multi-endpoint routing, load balancing, privacy-preserving access, and credentialed capability assertions. Our architecture design delivers five concrete guarantees: (1) A quilt-like index proposal that supports both NANDA-native agents as well as third party agents being discoverable via the index, (2) rapid global resolution for newly spawned AI agents, (3) sub-second revocation and key rotation, (4) schema-validated capability assertions, and (5) privacy-preserving discovery across organisational boundaries via verifiable, least-disclosure queries. We formalize the AgentFacts schema, specify a CRDT-based update protocol, and prototype adaptive resolvers. The result is a lightweight, horizontally scalable foundation that unlocks secure, trust-aware collaboration for the next generation of the Internet of AI agents, without abandoning existing web infrastructure.

Editor's note: This analysis is part of The Atlantic's investigation into the OpenSubtitles data set. You can access the search tool directly here. Find The Atlantic's search tool for books used to train AI here. For as long as generative-AI chatbots have been on the internet, Hollywood writers have wondered if their work has been used to train them. The chatbots are remarkably fluent with movie references, and companies seem to be training them on all available sources.

Customer Relationship Management (CRM) systems are vital for modern enterprises, providing a foundation for managing customer interactions and data. Integrating AI agents into CRM systems can automate routine processes and enhance personalized service. However, deploying and evaluating these agents is challenging due to the lack of realistic benchmarks that reflect the complexity of real-world CRM tasks. To address this issue, we introduce CRMArena, a novel benchmark designed to evaluate AI agents on realistic tasks grounded in professional work environments. Following guidance from CRM experts and industry best practices, we designed CRMArena with nine customer service tasks distributed across three personas: service agent, analyst, and manager. The benchmark includes 16 commonly used industrial objects (e.g., account, order, knowledge article, case) with high interconnectivity, along with latent variables (e.g., complaint habits, policy violations) to simulate realistic data distributions. Experimental results reveal that state-of-the-art LLM agents succeed in less than 40% of the tasks with ReAct prompting, and less than 55% even with function-calling abilities. Our findings highlight the need for enhanced agent capabilities in function-calling and rule-following to be deployed in real-world work environments. CRMArena is an open challenge to the community: systems that can reliably complete tasks showcase direct business value in a popular work environment.